Yakai Zhang

GFANet: Group Fusion Aggregation Network for Real Time Stereo Matching

Existing 3D stereo networks with 4D volumes are computationally expensive but precise while 2D stereo networks are efficient but poor performance. In this letter, we present a novel group fusion aggregation (GFA) for 2D convolutions cost aggregation based on 4D volumes to reduce computational costs.